# Adversarial Attack on DL-based Massive MIMO CSI Feedback

arXiv: https://arxiv.org/abs/2002.09896 · HTML: https://mlsanity.com/paper/2002.09896/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Feb 2020.

## Built on by (most cited first, 9 of 9)

- [Overview of Deep Learning-based CSI Feedback in Massive MIMO Systems](https://mlsanity.com/paper/2206.14383/) (2022)
- [CAnet: Uplink-aided Downlink Channel Acquisition in FDD Massive MIMO using Deep Learning](https://mlsanity.com/paper/2101.04377/) (2021)
- [Binarized Aggregated Network with Quantization: Flexible Deep Learning Deployment for CSI Feedback in Massive MIMO System](https://mlsanity.com/paper/2105.00354/) (2021)
- [Security Concerns on Machine Learning Solutions for 6G Networks in mmWave Beam Prediction](https://mlsanity.com/paper/2105.03905/) (2021)
- [Adversarial Machine Learning Threat Analysis and Remediation in Open Radio Access Network (O-RAN)](https://mlsanity.com/paper/2201.06093/) (2022)
- [Aggregated Network for Massive MIMO CSI Feedback](https://mlsanity.com/paper/2101.06618/) (2021)
- [Enhancing O-RAN Security: Evasion Attacks and Robust Defenses for Graph Reinforcement Learning-based Connection Management](https://mlsanity.com/paper/2405.03891/) (2024)
- [A Robust Adversarial Network-Based End-to-End Communications System With Strong Generalization Ability Against Adversarial Attacks](https://mlsanity.com/paper/2103.02654/) (2021)
- [A Streamlit-based Artificial Intelligence Trust Platform for Next-Generation Wireless Networks](https://mlsanity.com/paper/2211.12851/) (2022)

## Abstract (arXiv)

With the increasing application of deep learning (DL) algorithms in wireless communications, the physical layer faces new challenges caused by adversarial attack. Such attack has significantly affected the neural network in computer vision. We chose DL-based analog channel state information (CSI) to show the effect of adversarial attack on DL-based communication system. We present a practical method to craft white-box adversarial attack on DL-based CSI feedback process. Our simulation results showed the destructive effect adversarial attack caused on DL-based CSI feedback by analyzing the performance of normalized mean square error. We also launched a jamming attack for comparison and found that the jamming attack could be prevented with certain precautions. As DL algorithm becomes the trend in developing wireless communication, this work raises concerns regarding the security in the use of DL-based algorithms.